MD Simulation Investigation on the Binding Process of Smoke-derived

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Computational Biochemistry

MD Simulation Investigation on the Binding Process of Smoke-derived Germination Stimulants to Its Receptor Fei Hu, Xiao-Ting Liu, Jilong zhang, Qingchuan Zheng, Roberts I. Eglitis, and Hong-Xing Zhang J. Chem. Inf. Model., Just Accepted Manuscript • DOI: 10.1021/acs.jcim.8b00844 • Publication Date (Web): 18 Mar 2019 Downloaded from http://pubs.acs.org on March 19, 2019

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Journal of Chemical Information and Modeling

MD Simulation Investigation on the Binding Process of Smoke-derived Germination Stimulants to Its Receptor Fei Hua, Xiao-Ting Liua, Ji-Long Zhanga*, Qing-Chuan Zhenga, Roberts I. Eglitisb, and Hong-Xing Zhanga* a

International Joint Research Laboratory of Nano-Micro Architecture Chemistry, Institute of Theoretical Chemistry, Jilin University, Changchun 130023, Jilin, People’s Republic of China.

b Institute

of Solid State Physics, University of Latvia, 8 Kengaraga Str., Riga LV1067,

Latvia. *To whom correspondence should be addressed. E-mail: [email protected]; [email protected]. Tel: +86-431-88498966. Fax: +86-431-8945942.

ACS Paragon Plus Environment

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Abstract: Karrikins (KARs) are a class of smoke-derived seed germination stimulants with great significance in both the agriculture and plant biology. By means of direct binding to the receptor protein KAI2, the compounds can initiate the KARs signal transduction pathway, hence triggering germination of the dormant seeds in the soil. In the research, several molecular dynamics (MD) simulation techniques were properly integrated to investigate the binding process of KAR1 to KAI2 and reveal the details of the whole binding event. The calculated binding free energy, -7.00 kcal/mol, is in good agreement with the experimental measurement, -6.83 kcal/mol. The obtained PMF profile indicates the existence of three intermediate states in the binding process. The analysis of the simulation trajectories demonstrates that, in the intermediate structures, KAR1 is stabilized by some hydrophobic residues (Phe26, Phe134, Leu142, Trp153, Phe157, Leu160, Phe194), along with several bridging water molecules, and meanwhile the significant shifting occurs in the local conformation of the protein as the ligand’s binding. A series of the residues (Gln141-Phe157) on the so-called “cap domain” are proposed to be responsible for capturing the ligand at the initial stage of the binding. Besides, the changes of the ligand’s poses are also quantitatively characterized by the proper choice of the coordinate system. Our work will contribute to the more penetrating understanding of the ligand binding process and the receptor affinity difference between several members in the KARs family and help design new more effective germination stimulants.


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1. Introduction Smoke derived from burning plant material has now been well established as a broadly effective stimulant that enhances seed germination of approximately 1,200 species in more than 80 genera worldwide.1,2 As the discovery of the primary germination stimulant, 3-methyl-2Hfuro[2,3-c]pyran-2-one (KAR1),3,4 a family of structurally-related compounds in smoke was subsequently identified as plant growth regulators, and has now been named as karrikins (KARs) (Fig.1).5 As shown in Fig.1, the chemical structures of KARs are characterized by a 5membered lactone, butenolide, and a fused 6-membered pyran ring, both of which are strictly required for their biological activity.6,7 KARs can strongly enhance germination of dormant seeds of the model plant, Arabidopsis thaliana, in the light- and gibberellin-dependent manner.8,9 For some species, the signal molecules are still bioactive at concentrations as low as 1 nM,3,10 which is far more effective and sensitive than known phytohormones or the structurally related synthetic strigolactone (SL) analog, GR-24 (Fig. 1). In addition to seed germination stimulation, KARs also have a positive effect on seedling photomorphogenesis, including the inhibition of hypocotyl elongation, and the promotion of cotyledon expansion and greening.9, 11 Besides, KARs are speculated to enhance the seedling vigor under stressful growth conditions, such as high temperature, drought and salt stress.12-18 In consideration of the striking functions in plant physiology, KARs show significant potential in a variety of plantmanagement contexts, such as promoting seed germination and seedling growth of crops, inhibiting the breeding and spreading of weeds, restoring degraded lands. All of these applications will provide great benefits for agriculture, horticulture, mining, and the protection of natural ecology. Recently, some new evidences imply that as exogenous signaling molecules, KARs may mimic an endogenous but yet unidentified phytohormone which is expected to share similar structural features, and even physiological functions, with karrikins.11,19-22 Considering the physiological relevance of KARs among angiosperms, the significance of these signaling molecules could extend far beyond previously realized fire ecology and the relevant agricultural applications and will be more and more embodied in the researches aimed at revealing the evolutionary and physiological functions of angiosperms.


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Fig. 1. Chemical structures of KARs family and synthetic strigolactone analog, GR-24. Genetic and biochemical studies, along with X-ray crystallographic experiments, have demonstrated that the protein responsible for the perception of KARs in plant is KARRIKIN INSENSITIVE 2 (KAI2), previously also known as HYPOSENSITIVE TO LIGHT (HTL) due to its sensitivity to light of all wavelengths in seedling photomorphogenesis.11,19,22-26. KAI2 is a member of the α-/β-fold hydrolase superfamily that commonly possess a conserved catalytic triad of Ser(Cys)-His-Asp residues typical of hydrolytic enzymes of this class.27 The members of this hydrolase superfamily mainly participate in hormone signaling in relation to essential components such as gibberellin receptor GID1,28,29 salicylic acid binding protein SABP2,30,31 and the SL receptor DWARF14 (D14).23 Thereinto, KAI2 and D14 are the homologous proteins for the perception of KARs and the phytohormone SL, respectively.23 The two proteins function in parallel signaling pathways that share a requirement for the F-box protein MAX2/D3, but produce distinct growth responses by regulating different members of the SMAX1-LIKE/D53 family.32 KAI2’s paralogs in parasites have been classified into three phylogenetic clades



(conserved, intermediate, and divergent subclades) with different responses to KARs/SL, in which the divergent clade has been shown to undergo convergent evolution to D14 in host for SL recognition.33 The recent crystallography experiments have provided the detailed structural data of KAI2, which deepens our understanding of the molecular mechanism underlying the ligand recognition of KAI2.23-25,34,35 By the immediate comparison between apo- and holo-form of KAI2, it is inferred that the binding of KAR1 induces a conformational change of the protein at the active site entrance, reorienting a series of surface residues, and thus creates a contiguous interface for binding protein signaling partners in a ligand dependent manner.24,25 However, the static structural information fails to answer the questions about how the ligand binds to the receptor protein step by step and how the protein conformation gradually changes to capture the ligand into its active site. Therefore, little is still known about the detailed binding process of KARs to KAI2 and the receptor’s conformational changes. Molecular dynamics (MD) simulation has now developed into a mature technique which can be effectively used to study the dynamic properties of biologically relevant molecules and understand their structure-to-function relationships. Until now, however, no simulation work on the KAI2-KARs binding has been reported. In the present research, the detailed binding process of KAR1 to its receptor protein KAI2, together with the related binding energetics, was investigated by the proper integration of several MD simulation techniques which have been proven to be powerful in addressing the similar protein-ligand binding issues.36-39 On the basis of steered molecular dynamics (SMD) simulations, the adaptive biasing force (ABF) method was used to obtain the potential of mean force (PMF) of the binding process and reveal the conformational changes of the protein and the ligand. Our simulation results present a dynamic binding view of KAR1 to KAI2 and will be helpful for the more penetrating understanding of the physiological function of KARs signal molecules family and their receptor. 2. Computational Details 2.1 Preparation of Simulation System The initial coordinates of the present simulation system were obtained from the Protein Data Bank, PDB access code 4JYM. The three-dimension structure of KAI2 with the substrate KAR1 binding


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in the active site was derived from the X-ray crystallographic experiment of Arabidopsis thaliana KAI2 (AtKAI2).24 Because it has been experimentally determined that the biological unit of the enzyme is monomeric form, the chain B of the crystal structure was chosen for our present MD simulations. The crystal water molecules in the chain were also preserved. All the missing atoms in the experimental structure were automatically added by VMD psfgen plugin.40 In order to simulate the actual environment where the binding event happens, more TIP3P water molecules,41 extending up to 10 Å from the solute in each direction, were added by the solvate plugin in VMD, which forms a rectangular box with the size of 70×73×71 Å3. The salt concentration of the system was set to 154 mM, including 46 Na+ and 29 Cl-. The final system contains 33803 atoms.

2.2 Molecular Dynamics Simulations All the MD simulations were performed by the parallel MD package NAMD 2.12.42 The system constructed above was first subjected to the conventional MD simulation to achieve the equilibrium. Topology and force field parameters for the protein were assigned from the CHARMM36 protein parameter set.43 The force field parameters for the ligand KAR1 were developed with the aid of the Force Field Toolkit (ffTK) plugin in VMD.44 The van der Waals (VdW) parameters for each atom in the ligand were from the CHARMM General Force Field (CGenFF) parameter set.45 The initial values of other force field parameters, involving bonds, angles, dihedrals, and charges, were derived from the necessary quantum mechanical (QM) calculations using the Gaussian 09 package.46 In the QM calculations, the geometry optimizations and relaxed potential energy scans were performed at the MP2/6-31G* level, while the computations of the interaction energy between the ligand and water molecules were carried out at the HF/6-31G* level to maintain consistency with the CHARMM force field. The charge and spin multiplicity for the ligand’s structural optimization were set to 0 and 1, respectively. The other settings for the force field development remain default in the ffTK plugin. In all MD simulations, periodic boundary conditions were applied to the whole system to avoid boundary effects caused by finite size. The van der Waals and short-range electrostatic interactions were gradually turned off at a distance range between 10 and 12 Å. The particle mesh Ewald (PME) method was employed for the computation of the long-range electrostatic interactions.47 The pair list distance was 14 Å and the corresponding non-bonded pair list was updated every 20 steps. An



integration time step was set to 1 fs. The whole simulation system was first energy minimized with 20000 steps of conjugate gradients, by restraining the positions of the protein backbone and ligand atoms with a force constant of 10 kcal mol-1 Å-2. After that, at the same restraint, the temperature of the system was gradually increased from 100 to 300 K with Langevin thermostat at an increment rate of 1 K per 2ps.48 Then, an additional 1 ns MD simulation was performed to ensure the stability of system’s temperature in the canonical (NVT) ensemble. During the period, the constraint potential was gradually decreased to zero at a rate of 2 kcal mol-1 Å-2 per 200 ps. Following that, the simulation system without any restraint was subjected to another 20 ns equilibrium MD simulation in the constant pressure/constant temperature (NPT) condition, in which the pressure of the system was coupled to a reference pressure of 1 bar with modified Nose-Hoover Langevin piston method.49 Then the time step of 2 fs was used for the further 80 ns free NPT MD equilibrium simulation, with all bonds involving hydrogen atoms constrained by SHAKE algorithm. The final equilibrated conformation was chosen as a restart point for the next SMD simulation.

2.3 Steered Molecular Dynamics Simulation In the present research, SMD simulation was performed to explore the binding pathway of KAR1 to KAI2 and yield the initial coordinates for the ABF calculations. SMD simulation is a computational approach which is designed to mimick atomic force microscopy (AFM),50 optical tweezer,51 biomembrane force probe, and surface force apparatus experiments. In SMD simulation, timedependent external forces are applied to facilitate the unbinding of a ligand from its receptor. The recording of externally applied force and ligand’s position (as a function of time), as well as the analysis of the interactions of the dissociating ligand with the receptor, can provide a large amounts of important structural information about the structure-function relationships of the ligand-receptor complex and mechanism underlying the selectivity of the receptor. In the NAMD implement, SMD simulation can be carried out by either constant force (cf) or constant velocity (cv) manner. In the former a constant force is applied to an atom (or set of atoms), and in the latter a harmonic (springlike) restraint is attached to one or more atoms of the system.42 Here, the cv-SMD was adopted on the basis of the equilibrium conformation from the above conventional MD simulation. A force constant of harmonic restraint and a pulling velocity were set to 0.2 kcal mol-1 Å-2 and 5 Å ns-1, respectively. Through several tests, combined with our previous works,36-39 we confirmed that the


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two parameters are suitable for the present simulation about the unbinding of KAR1. While keeping the alpha-carbon (Cα) atoms of three residues (Ser31, Leu77, and Ala102) fixed, external steering force was exerted on the center of mass (COM) of the ligand KAR1 along the direction determined by the vector from the CG atom (atom name in the force field file) of Leu77 to the O10 atom of the ligand. The steering force experienced by the reference point was calculated by employing Eq. 1 as follow:

  F (t )  k (v t  r ) where k is the force constant of harmonic restraint and

(1)

 r is the displacement of the reference

point from its original position. During the SMD simulations, the external force was only applied along the pulling direction. The ligand was free from constraint in the plane perpendicular to the pulling direction. A 2 fs time step was used in the SMD simulations. The trajectory was saved for every 4 ps, and the steering force was recorded for every 40 fs. The total 12 ns SMD simulation for each run was performed to ensure the complete dissociation of the ligand from the active site of the receptor. The same simulations were repeated four times with the different random seeds. Then the obtained SMD trajectories were selectively extracted for the PMF calculations.

2.4 Potential of Mean Force Due to the need of a large amount of spatial exploration, the simulations of a ligand binding process and the associated energy calculations greatly challenge the sampling process, and therefore longtimescale MD simulations should be performed.52 In our present work, in order to investigate the energetics of the binding of KAR1 to the receptor KAI2, the PMF profile corresponding to the binding process was calculated by means of long-time simulation sampling for conformation space. First, a reaction coordinate (RC), ξ, was defined as the distance between the COMs of the ligand KAR1 and the receptor KAI2. The PMF, ΔG(ξ), along ξ was determined by the ABF method.53 In the NAMD implementation of ABF,54 the average force acting on the RC is evaluated within the classical thermodynamic integration formalism.55 The free energy derivative, dG(ξ)/dξ, is estimated locally throughout the simulations, thus yielding a continuous update of the biasing force. Once applied to the system, the bias can provide a Hamiltonian in which no net average force acts along ξ. As a result, all the RC values are sampled with the same probability, which greatly improves the



accuracy of the free energy calculations. To further increase the computation efficiency, the RC ranging from 7.9 to 30 Å was divided into 44 windows with 0.1 Å overlap of two adjacent windows. For each window, taking the coordinates from the above SMD simulation as the initial input, up to 50 ns sampling was performed after 10 ns equilibrium simulation. Instantaneous values of the force were accrued in bins with 0.01 Å wide. Finally, an additional simulation was carried out for the combination of energy data from all the separate runs. The convergence of PMF calculations was probed by extending the simulation time of each window and assessing the evolution of the free energy as a function of time.

2.5 Analysis of the Ligand Pose’s Change First of all, the representative conformation in the trajectories related to each intermediate were selected on the basis of the ligand’s RMSD values relative to its average structure after the structural alignment of protein’s backbone. The pose of the ligand with respect to the receptor, involving the relative position and orientation, will certainly undergo great changes in the binding or unbinding process. In order to quantitatively characterize the changes, we constructed a coordinate system of the ligand relative to the receptor by choosing three atoms in both KAR1 and KAI2. The three atoms in the receptor are the Cα atoms of the residues 246, 76, and 63, designed as P1, P2, and P3, respectively. In the ligand, the chosen three atoms designed as L1, L2, and L3 are the carbon atom of the methyl group (numbered 9 in Fig. 1), the oxygen atom of the carbonyl group (numbered 8), and the oxygen atom in the 6-membered ring (numbered 6), respectively. The Euler angles used to define the orientation of KAR1 relative to KAI2 are the P1-L1-L2 angle Θ, the P1-L1-L2-L3 dihedral angle Φ, and the P2-P1-L1-L2 dihedral angle Ψ. The spherical coordinate system needed to establish the position of KAR1 relative to KAI2 comprises, the distance between the COMs of the ligand and the receptor, the L1-P1-P2 angle θ, and the L1-P1-P2-P3 dihedral angle ϕ. On the basis of the constructed coordinate system (see Fig. S1), we can clearly present the pose’s change of the ligand with respect to the receptor. Here, it should be realized that the choice of the present reference atoms is arbitrary and whichever reference coordinate system can be used to quantitatively depict the change in the ligand’s binding/unbinding process. The only difference between these reference choices is to produce the diverse order parameters and the corresponding values. It should be specially mentioned that the present scheme for characterizing the alteration of the ligand’s pose


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takes the structural rigidity of the ligand as the premise, otherwise the variables defined above will, to a large extend, lose their due meaning. As demonstrated below, the ligand’s structure shows great rigidity during the MD simulations. Therefore, we can quantitatively describe the relative change of the ligand’s pose using the present coordinate system.

3. Results and Discussion 3.1. Equilibrium of the System The conventional MD simulation was performed to acquire the adequately equilibrated complex and explore the equilibrium characteristics of the system. The protein’s structural stability was assessed by monitoring the time dependence of the root-mean-square deviation (RMSD) values of all the heavy atoms. It can be seen from Fig. S2 that with respect to the initial crystal structure, the RMSD values of all the non-hydrogen atoms are stabilized near 1.35 Å after a very short simulation time. This shows that the protein’s conformation has been in the stable state. Besides, we also calculated the root-mean-square fluctuation (RMSF) values for the protein’s Cα atoms at the equilibration simulation stage. The obtained results are shown in Fig. S3. It can be noted from the figure that there exist three flexible regions in the protein. The structural inspection show that each of them belongs to one of the loop regions located on the protein’s surface and exposed to the solvent. Therefore, their large RMSF values are not unexpected because of the structural characteristics of a loop region and the effect of the solvent. The last two of the three regions are part of a so-called “cap domain” which is considered to play an important role in the ligand’s stabilization.25 In particular, the one consisting of the residues 162-171 might also participate in the interaction of KAI2 with the downstream F-box protein MAX2/D3 in the KARs signal pathway, which could be speculated from the KAI2’s structural comparison with the homologous protein D14 because the crystallographic experiments have obtained the structure of Arabidopsis thaliana D14 (AtD14) complexed with D3.56 Under the circumstances, the flexibility of the region might greatly affect the binding affinity of KAI2 with D3 and even determine the function of KAI2. Another flexible region from Tyr124 to Phe134 directly includes part of the active site residues and is expected to have greater influence on the ligand’s binding. Besides, all the residues in the range of 4 Å near the ligand don’t have very high RMSF values (less than 0.56 Å), which originates partly from the rigid



structure of the active site and partly from the stabilization effect of the ligand’s binding. The RMSD values of the heavy atoms of the ligand KAR1, with the average value of 0.09 Å, are much smaller than the RMSD values of the protein’s heavy atoms, which can be attributed to the rigidity of the ligand’s structure to a large extend.

3.2. Time Dependence of the Steering Force The complete binding or unbinding event of a ligand to its receptor is, even in today’s computing power, still difficult to be fully presented in the time scales of conventional MD simulation. Thus, SMD simulation technique was used to accelerate the binding or unbinding process in order to investigate all the binding details of KAR1 to the receptor protein KAI2. In the present research the cv-SMD simulations have produced the time evolution profile of external steering force and the system’s dynamic pictures in the unbinding process, the reverse process of the binding. Fig. 2 shows the changing curves of the external force from four repeated SMD simulations. It can be seen from the figure that the pulling force exerted on the ligand keeps linear increase at the initial stage of the dissociation process. After a period of time, the increase rate of the steering force drops slightly in the time range of 5-6 ns. After that, the force curves reach its peak values with the average of 225 pN near 7 ns. At the moment, the ligand is about to dissociate from the receptor. Then the value of the steering force rapidly decreases to zero and fluctuates around zero, which reflects the motion of the ligand in solvent and proves its complete separation from the receptor. On account of the position and structural characteristics of the binding site of KAR1 in the receptor, the pulling direction for the ligand’s unbinding has no more choices. The pulling tests along the other different directions show that compared with the currently chosen direction, the peak values of pulling force increase significantly when the direction angle changes more than 5 degrees, that is, the other directions give much larger peak values, which implies the unfavorable unbinding pathway. It should be noted that the SMD simulations can provide the initial conformations for the further PMF calculations and give some important hints for the key intermediate states in the binding/unbinding process in spite of the inherent inadequacy of the present SMD sampling.


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Fig. 2. Time dependence of the external force in four repeated SMD simulations. The different colors of the curves are used to distinguish the results from four SMD simulations. 3.3. Potential of Mean Force The PMF for the binding process of KAR1 to KAI2 has been obtained by the total 2.64 μs ABF calculations. The time evolution of the free energy profile was shown in Fig. S4. It is obvious that the PMF curves have converged after 44 ns sampling simulation for each window. The two free energy curves from 48 and 50 ns simulations almost completely coincide with each other. Here, the PMF curve of 50 ns sampling (Fig. 3) was used for analysis. It can be seen from this figure that the calculated binding free energy of KAR1 to KAI2 is -7.00 kcal/mol, in good agreement with the experimentally estimated value of -6.83 kcal/mol.24 If the temperature difference between simulation (300 K) and experiment (296.15 K) is further considered, our calculation result is closer to the experimental measurement (ΔΔG < 0.1 kcal/mol), which illustrates the reliability of our simulations.



Fig. 3. Free energy profile in the binding process of KAR1 to its receptor KAI2. The translucent red shadow region on the black energy curve stands for the error. The final PMF profile in Fig. 3 has shed light on some important intermediate states, apart from the stable complex state, during the binding process of KAR1 to its receptor. A closer look at the profile reveals that the global minimum of free energy locates at 9.9 Å, corresponding to the most stable ligand-receptor binding state from the X-ray crystallographic measurement. This point is set to the reference zero point of the PMF profile. Less than the RC value, the free energy curve rapidly rises due to the repulsion between KAR1 and KAI2. Greater than 9.9 Å, the free energy value also increases as the ligand departs from the stable equilibrium position, which is attributed to the interaction of the ligand with the active site residues. When the RC approaches the position of 12.0 Å, the first local minimum of PMF appears, with a free energy of about 2.76 kcal/mol relative to the reference zero point. The atomic interaction of the ligand with the relevant residues will be in detail discussed below. After the first local minimum, the free energy curve continues to increase until the RC reaches the position of 15.3 Å where the complex system change to the conformation with the second local minimum. The relative energy value at this point is 3.44 kcal/mol. The third intermediate state during the unbinding process emerges in the position of 20.5 Å where the relative


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energy value is 4.42 kcal/mol. Following that, the PMF profile keeps rising till the ligand totally dissociates from the active site and enters the solvent environment. The inspection of the MD trajectories shows that when the RC locates at 30 Å, the ligand has little interaction with the protein. Combined with some previous researches on the other known ligands,37-39 the most noteworthy question in the binding process of KAR1 to KAI2 is that there exist three intermediate states prior to the final stable complex state, which illustrates the complexity of the ligand to the receptor. Next, we will in detail analyze the atomic interaction in the key intermediate structures.

3.4. Structures of Three Intermediate States The ligand-receptor interaction mode corresponding to the first local minimum in the PMF profile is shown in Fig. 4(a). In the intermediate state, the Euler angles defining the orientation of KAR1 relative to KAI2, Θ, Φ, and Ψ, have changed to 13°, 16°, and 178° from 52°, -119°, and -96° in the stable complex state, respectively (Table 1). This shows the rotation of the ligand relative to the initial stable conformation. Two polar angles θ and ϕ also alter to a certain extent, from 51° and 44° to 95° and 22°, respectively. In terms of protein’s residues, the benzene rings of Phe194, Phe26, and Phe134 has flipped about 145°, 30°, and 90° with respect to the stable binding state. The conformation of Phe157 changes very little in the present intermediate. The side chain of Leu218 does no longer interact with KAR1 and turns to point towards the direction away from the ligand. There are no direct hydrogen bond (H-bond) interactions between KAR1 and KAI2. Two water molecules, however, bridge the ligand and some residues by H-bonds. One water appears between KAR1 and Leu160, hydrogen bonding with the carbonyl oxygen atom of the ligand and the mainchain carbonyl oxygen atom of Leu160. The other water molecule simultaneously forms the Hbonds with the oxygen atom in the six-member ring of the ligand and the nitrogen atom in the imidazole ring of His246. Taken together, the hydrophobic effect from the residues Phe194, Phe26, and Phe134, along with the bridging H-bonds of the water molecules, stabilizes the ligand in the first intermediate state.



Fig. 4. Three intermediate structures in the binding pathway of the ligand to the receptor.


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Table 1 The values of all the variables from the defined coordinate system of the ligand relative to the receptor in the key complex states. Θ*

Φ

Ψ

θ

ϕ

ξ

Stable Complex State

52

-119

-96

51

44

9.9

1st Intermediate State

13

-16

178

95

22

12.0

2nd Intermediate State

22

130

-130

107

36

15.3

3rd Intermediate State

59

168

82

84

7

20.5

*All the angles are in degree.

The second local minimum in the ligand’s unbinding process corresponds to the intermediate structure shown in Fig. 4(b). In the present state, the ligand further dissociates from the active site of the protein, which induces the changes of both the ligand’s pose and the orientation of some key residues, even the local conformation of the protein. First, the Type 1 β turn, consisting of the residues Asp217-Leu218-Ala219-Val220, shows a considerable shifting with the RMSD value of 1.7 Å for the backbone atoms and the RMSD of 2.4 Å for all the heavy atoms. (Here, the RMSD values are evaluated with respect to the stable complex structure on the basis of best structure superimposition for the entire protein.) In fact, the shifting of the β turn has occurred in the first intermediate state but is not so obvious as in the present intermediate. The structural inspection reveals that the reason why all-atom RMSD is larger than the backbone RMSD for the β turn mainly lies in the side chain deviation of the residue Leu218. The present conformation of the residue is similar to that in the first intermediate state. The side chain conformation of the other residues in the β turn doesn’t exhibit any significant changes. Another remarkable residue is Phe194 which is considered as the residue with most pronounced conformational change as KAR1 binding.24 In the present intermediate, the side chain of the residue rotates about 80° with respect to the stable ligandreceptor binding state. In this case, the conformation of its benzene ring is almost identical to that in the apo-protein obtained experimentally. In other words, our MD simulations have reproduced the experimental observations, which also verifies the feasibility and credibility of the MD simulations in dealing with the present system. Besides, the aromatic rings of the residues Phe157



and Phe134 have also a slight rotation with the rotation angles of 30° and 10°, respectively. A water molecule simultaneously forms the H-bonds with the carbonyl oxygen atom of the ligand and the carboxyl oxygen atom in the side chain of Asp217. The residue is anchored via H-bond by the main chain of Val220 and the side chain of His246. In the intermediate, the ligand’s pose undergoes new changes as its dissociation from the active site (see Table 1). When the complex structure is in the last intermediate during the unbinding process (Fig. 4(c)), the ligand KAR1 resides on the surface of the receptor and is embraced by several hydrophobic residues, Phe157, Trp153, Leu142, Phe134, and Leu160. While contacting with these residues by its hydrophobic side, KAR1 also uses the oxygen-bearing edge to keep some additional connections to the residues Gln141 and Asp138 via two or three floating water molecules (not shown). The detailed orientation parameters for this pose can be found in Table 1. In the intermediate state, the helix parts composed by the residues 141-157 show the significant shifting in comparison with the conformation in the stable complex state (see the blue tube representation in Fig. 4(c)). The RMSD value for this part of protein with respect to the conformation in the stable state is up to 2.5 Å while the side chain conformations of the relevant residues have no obvious difference. Therefore, the large RMSD mainly originates from the whole relative motion of the protein’s portion. The region of the protein belongs to a so-called “cap region” proposed as the gate-keeper in the previous research.25 Here, our simulation illustrates that the portion is used to capture the ligand at the initial stage of ligand’s binding, thus leading to the emergence of a local minimum in the PMF profile. Besides, the side chain of Phe194 still maintains the same conformational state as that in the experimental structure.

3.5. Validation and Application of the Proposed Binding Process It should be first addressed that the ligand’s binding to the receptor is a complex process in which the ligand’s pose and the conformation of the relevant residues are in a continuous motion. And, the important intermediate states in the ligand binding process is difficult to be captured in the experiment, but MD simulation provides us with an important approach to predict their existence and explore the ligand binding process. The reliability of the results can be verified by experiments. The present simulation predictions are consistent with the previous experimental results. First, the conformational change of the side chain of Phe194 observed in the experiment are completely


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reproduced by our simulation, with more detailed information.24 And our simulations also dynamically exhibit the movement of the “cap region” propose by the experiment.25 Furthermore, the mutation of the residue Ala219 in the important β turn shown by our simulation has been experimentally proven to impair ligand binding and downstream signal transmission.22 All the experimental results, along with the measurements of the dissociation constants,24 are in agreement with our theoretical predictions, which demonstrates the accuracy of the present simulations. On the basis of the intermediate structures mentioned above, we will summarize the binding process. At the initial stage of the binding event, the conformation of the “cap region” of the protein changes to capture the ligand to the surface of the receptor. After that, the nonpolar edge of the ligand keeps the hydrophobic interaction with several relevant nonpolar protein’s residues, especially the aromatic residues, which anchors the nonpolar edge of the ligand. The oxygen-bearing edge of the ligand interacts, by the bridging waters, with the polar amino acid residues in the binding pathway, which induces the changes of the ligand’s poses and the protein’s conformations (especially the β turn Asp217-Leu218-Ala219-Val220) from one intermediate conformation to another, until the final stable conformation. In a word, the hydrophobic effect is responsible for stabilizing the ligand while the hydrophilic interaction contributes to the adjustment of the ligand’s poses. The above analysis of the binding process could be used for explaining the different binding activities of some members in the KARs family.8 KAR2, without any methyl group (Fig. 1), can better define the aromatic-aromatic interactions with the aromatic residues of the protein, and thus is the most active analog for AtKAI2. The substitution of the methyl group(s) on KAR1 or KAR3 can disturb the aromatic effect but maintain the hydrophobic interactions with the relevant residues, so both of them are slightly less effective. And KAR4 has a methyl substitution in the oxygenbearing edge of the ligand, which could damage the polar interaction between the ligand and the related residues, hence the member in KARs family has the lower activity. According to the above comparison and analysis, it is proposed that the substitution of some hydrophilic groups on the oxygen-bearing side could lead to the germination stimulants with the higher affinity with the receptor protein.



4. Conclusions In the work, several MD simulation techniques were effectively integrated to investigate the entire binding process of the plant seed germination stimulant derived from smoke, KAR1, to its corresponding receptor protein, KAI2. The calculated result of binding free energy is in good agreement with the experimental measurement, which verifies the reliability of the simulation methods. The PMF profile based on the ABF calculations further indicates the existence of three intermediate states in the binding/unbinding process of the ligand. By the further inspection of simulation trajectories, we have in detail analyzed the interactions between the ligand and the receptor and proposed the key residues in these intermediate structures. Overall, the hydrophobic interaction dominates the ligand’s binding to the receptor. Three aromatic residues, Phe26, Phe134, and Phe194, along with the residue Leu218, are responsible for the stabilization of the ligand in the later stage of the binding. In the initial stage, the residues Phe157, Trp153, Leu142, Phe134, and Leu160, play more important roles for the ligand’s capture. Some bridging water molecules can also stabilize the ligand by the simultaneous H-bonds with the ligand and the relevant residues in the intermediate states. The protein’s conformation correspondingly changes as the ligand’s binding. First, a “cap region” previously considered as the gate-keeper is proposed to capture the ligand by the significant conformational alteration. Following that, the β turn consisting of the residues Asp217-Leu218-Ala219-Val220 shows the obvious shifting, further advancing the binding process. Besides, the alteration of ligand’s poses is also quantitatively represented by the proper choice of the coordinate system, which clearly presents the entire process of the ligand’s binding to the receptor.

Author Information Corresponding Author *E-mail: [email protected];[email protected].

Notes The authors declare no competing financial interests.


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Acknowledgment

This work is supported by the Natural Science Foundation of China (Grant No. 21203072) and the China Postdoctoral Science Foundation (Grant Nos. 2013T60320, 2013M541289). Dr. Ji-Long Zhang gratefully acknowledges the financial support provided by the International Postdoctoral Exchange Fellowship Program (Grant No. 20130037) and the Excellent Young Teacher Training Program of Jilin University.

Associated Content Supporting Information This information is available free of charge via the Internet at http://pubs.acs.org. The document in the supporting information includes the contents as follows: the force field parameters of the ligand KAR1, definition of the ligand’s position and orientation, RMSD values of the ligand’s heavy atoms, RMSF values of KAI2’s Cα atoms, convergence of the PMF calculations. The video file named “LigandBindingProcess” presents the dynamic binding process of the ligand KAR1 to the receptor KAI2.

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Fig. 1. Chemical structures of KARs family and synthetic strigolactone analog, GR-24. 145x288mm (300 x 300 DPI)


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Fig. 2. Time dependence of the external force in four repeated SMD simulations. The different colors of the curves are used to distinguish the results from four SMD simulations. 254x176mm (300 x 300 DPI)



Fig. 3. Free energy profile in the binding process of KAR1 to its receptor KAI2. The translucent red shadow region on the black energy curve stands for the error. 254x176mm (300 x 300 DPI)


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Fig. 4. Three intermediate structures in the binding pathway of the ligand to the receptor. 199x88mm (300 x 300 DPI)





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MD Simulation Investigation on the Binding Process of Smoke-derived

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